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The economic impact of depression: Resistance or severity?
European Neuropsychopharmacology (2010) 20, 671–675
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The economic impact of depression: Resistance or severity? L. Fostick a,⁎, A. Silberman b , M. Beckman c , B. Spivak c , D. Amital c a
Ariel University Center of Samaria, Israel Department of Psychiatry, Chaim Sheba Medical Center, Israel c Ness-Ziona Mental Health Center, Israel b
Received 18 April 2010; received in revised form 3 June 2010; accepted 9 June 2010
KEYWORDS Major Depressive Disorder (MDD); Treatment-Resistant Depression (TRD); Severity; Economic burden
Abstract Treatment-Resistant Depression (TRD) affects 60 to 70% of patients with Major Depressive Disorder (MDD). The economic impact of depression in general, and of TRD specifically, was found to be relatively high. As the course of depression can be defined both by the severity of the disease and by the resistance to treatment, the question of the unique contribution of MDD severity vs. resistance to the economic burden of depression is being raised. One hundred and seven unipolar MDD patients, all treated for at least 4 weeks, were enrolled in the study. Patients were assessed for their current MDD severity using the Hamilton Depression Rating Scale (HDRS) and past treatments, and for medical-related costs (number of blood and imaging tests, visits paid to physicians, psychiatric hospitalizations) and incapacity-related costs (number of working days lost) during the last episode. TRD and non-TRD patients were, respectively, 39.3% and 60.7% of the patients recruited for the study. TRD patients had more severe depression, and higher costs for imaging tests, physician visits, psychiatric hospitalizations, and number of working days lost. In addition, higher MDD severity was found to be associated with higher costs. Finally, when controlling for the shared variance of TRD and MDD severity, by using residual scores, TRD was associated with higher costs, but MDD severity was no longer related to costs. While both resistance and severity are associated with higher direct and indirect costs, our findings suggest that TRD may be the main factor in determining the economic burden of depression. © 2010 Elsevier B.V. and ECNP. All rights reserved.
1. Introduction
⁎ Corresponding author. Department of Communication Disorders, Ariel University Center of Samaria, 40700, Israel. Tel.: +972 3 9765776; fax: +972 3 9765743. E-mail address: [email protected] (L. Fostick).
Treatment-Resistant Depression (TRD) is a major publichealth problem, affecting the suffering patient, his close relatives, and society as a whole (Crown et al., 2002). TRD 12-month prevalence is estimated to be 2–3% (figures vary according to definition) (Nemeroff, 2007). Despite rapid
0924-977X/$ - see front matter © 2010 Elsevier B.V. and ECNP. All rights reserved. doi:10.1016/j.euroneuro.2010.06.001
672 development in the therapeutic tools of mood disorders since the late 1980s (Fredman et al., 2000; Kocsis, 2000), 60 to 70% of Major Depressive Disorder (MDD) patients fail to reach complete remission even when adequately treated (Sackeim, 2001). Moreover, about half of those who do respond to treatment and exhibit substantial decrease in their symptomatology continue to have significant residual symptoms that affect their functioning and quality of life. Therefore, TRD results in a substantial burden of escalating medical mental health costs and suffering. The economic burden of depression is a subject of public interest and is measured nationally among the economic burdens of other diseases. Not surprisingly, the economic burden of depression is very high, estimated at $83.1 billion in the US in 2000 (Greenberg et al., 2003), and at 7 billion pounds in the UK in 2000 (Thomas and Morris, 2003). More specifically, investigators who focused on the economic burden of TRD have estimated its costs to be approximately $11,000 to $14,000 per year (Corey-Lisle et al., 2002; Crown et al., 2002; Russell et al., 2004). While evaluating the economic cost of depression on society, investigators usually separate between direct costs, which are costs due to the treatment of depression, and indirect costs, which are costs due to the impact of depression, such as loss of work productivity (work absenteeism and reduction of productivity within the work place) and suicide (Thomas and Morris, 2003; Kind and Sorensen, 1993; Greenberg et al., 1993). For example, of the total costs for depression estimated in the US in 2000, 31% ($26.1 billion) was related to direct medical costs, 7% ($5.4 billion) was related to suicide-related mortality costs, and 62% ($51.5 billion) was related to workplace costs (Greenberg et al., 1993). Work absenteeism is considered to be a major contributor to the economic burden of depression (Tierney, 2007). Along this line, Kessler et al. (1999) suggest that the costs of depression-related work absenteeism for a period of thirty days, alone, are almost as expensive as the total costs for successful treatment of depression. However, the studies that measure the impact of depression on work do not include estimates for the cost of loss of productivity while at work. Stewart et al. (2003) estimated an excess loss of productivity of $44 billion in the USA during 2000, solely due to the loss of productivity at the work place, without taking into account work absenteeism or disability pensions. Depression can take different courses. Whether moderate or severe, it may respond well to treatment, and therefore be of short duration. Conversely, it can last for years with no response, or more frequently with partial response to different treatment regimens. Depression severity and resistance may be considered to be separate and overlapping factors. Fava (2003) suggested that MDD with psychotic features, which might be considered a severe form of depression, is associated with poor treatment outcome, therefore causes a treatment resistant form of depression. However, some researchers have found melancholic depression, which can also be considered a severe form of depression, does not seem to be associated with poor response, and therefore causes a severe, but not resistant, form of depression (Joyce et al., 2002), while others have found both melancholia and MDD severity to be associated with TRD (Souery et al., 2007). The partition between these
L. Fostick et al. two forms of depression raises the question whether the relatively large economic burden of depression is related to the severity of the depression, i.e. to the magnitude of functional impairment and loss of productivity, or rather to the chronicity of the disease among the significant number of the patients who are resistant to treatment? Reviewing the existing literature on the economic impact of depression, this question remains unanswered. The literature employs different definitions of TRD, based the number of failed adequate treatments the patient received (Thase and Rush, 1997; Fava, 2003; Souery et al., 1999). In 2002, the European Union's Committee for Propriety Medicinal Products (CPMP) defined TRD as a failure to respond to the second treatment of two consecutive products of different classes given at an adequate dose and for a sufficient length of time. This definition was adopted in the current study as it enables the differentiation of MDD patients into two groups, according to their response to treatment. In the current study we aim to explore the economic impact of TRD, focusing on both direct and indirect costs. As opposed to previous studies that addressed this issue (e.g., Crown et al., 2002; Russell et al., 2004; Greenberg et al., 2003, 2004), the current study reports not only on costs related to TRD, but also on individual data of the severity of depression drawn from clinical interviews with each of the participants. These unique set of data will enable us to explore the differential contribution of chronicity vs. severity in the economic burden of TRD.
2. Experimental procedures Participants. The participants in this study were identified during 2005 from the registry of four community psychiatric outpatient clinics, providing psychiatric care to about 10,000 people. Among them, a total of 150 potential participants were found to meet the following inclusion criteria: lifetime diagnosis of unipolar depression according to ICD-10 (F32, F33); at least one adequate treatment, i.e., an optimal dose of the medication, according to the product datasheet, provided for a duration of at least 4 weeks (both responders and non-responders) during their last depressive episode; and no diagnosis of bipolar disorder, schizophrenia, severe neurological problems, or mental retardation. These criteria, along with demographics, were evaluated through medical records. The study psychiatrist (MB) called all 150 eligible patients by telephone. Among them, a total of 107 patients agreed to participate in the study and were invited to the clinic for an interview with the psychiatrist. Participants received a full explanation about the study and signed a written informed consent prior to the interview. The study protocol was approved by the local ethics committee. Assessment. All clinical ratings were administered during a single interview by the study psychiatrist (MB) who was trained in the study procedure and was blind to the study aim. The interviews lasted for 45–60 min and took place after consultation with each patient's psychiatrist. To assess the current disorder, we used the Mini International Neuropsychiatric Interview (MINI; Sheehan et al., 1998) to verify current and lifetime diagnosis. Depression symptoms were evaluated by the 17-item Hamilton Depression Rating Scale (HDRS; Hamilton, 1960). Direct (medical-related) and indirect (incapacity-related) costs were assessed using a self-rating questionnaire, in which each patient indicated the number of blood and imaging tests he undertook, the number of physician visits, the number of psychiatric
The economic impact of depression: Resistance or severity? hospitalizations, and the number of working days lost during the last episode. Treatment costs were calculated based on the price list for medical utilization published by the Israeli Ministry Of Health (MOH) (MOH, 2006), combined with the patients' reported usage of MOH services. Workplace costs were calculated by multiplying the average missed working days per month during the current episode reported by the patient with the average income in Israel, which was $1633 per month in 2005 according to the Israeli Central Bureau of Statistics (CBS, 2006). MDD severity was evaluated using the Hamilton Depression Rating Scale (HDRS; Hamilton, 1960). The participants were divided into two groups according to their response to treatment. A failure to respond to the current treatment was defined as HDRS ≥ 17 at least after 4 weeks of treatment in an optimal dose, and a failure to respond to previous treatment trials was identified by change of treatment. TRD patients were those who did not respond to two or more treatments from different mechanisms of action.
3. Results Table 1 presents TRD and non-TRD patients' demographic data (age, sex, and marital status), mean HDRS score, and costs (number of blood tests, number of imaging tests, number of physician visits, number of psychiatric hospitalizations, and number of working days lost during the last episode).
3.1. TRD and severity Age, sex and marital status did not differ between TRD and non-TRD patients. In order to test differences between TRD and non-TRD patients in severity measures, a Multivariate Analysis of Variance (MANOVA) was conducted with mean HDRS score as the dependent variable. MDD severity was found to be significantly different between TRD and non-TRD patients. Mean HDRS score was found to be higher among TRD (18.6) vs. non-TRD (9.8) patients.
Table 1
673
3.2. TRD and costs The difference between TRD and non-TRD patients in direct and indirect costs was analyzed using MANOVA, with total costs of blood tests, imaging tests, physician visits, psychiatric hospitalizations, and working days lost as the dependent variables. Overall, there was a significant difference between TRD and non-TRD patients in direct and indirect costs. When analyzing each parameter separately, costs for imaging tests, physician visits, psychiatric hospitalizations, and number of working days lost were found to be higher among the TRD group.
3.3. MDD severity and costs The relationship between MDD severity, as measured by HDRS, and costs, was measured using Pearson correlations between mean HDRS score and total costs of blood tests, imaging tests, physician visits, psychiatric hospitalizations, and working days lost. MDD severity was found to be associated with costs, as was reflected in significant positive correlations between mean HDRS score and all cost categories (Table 2).
3.4. TRD severity and costs As can be seen in Table 1, MDD severity is related to TRD so that higher severity was found among TRD patients. In order to estimate the contribution of TRD and MDD severity to costs, controlling for their shared variance (multicolinearity), we analyzed the relationship between costs and the residual scores for TRD and mean HDRS scores. Table 2 presents correlations between TRD residuals, mean HDRS residuals, and costs. TRD residuals were found to be significantly correlated with costs for blood tests, imaging tests, psychiatric hospitalizations, and physician visits, but not for working days lost. However, mean
Demographics, MDD severity, and costs, for TRD and non-TRD patients. TRD
Demographics Mean age (SD) Sex No. males (%) No. females (%) Marital status No. Single (%) No. married (%) No. divorced (%) No. widow/er (%) MDD severity Mean HDRS score Costs (in NIS) Blood tests (SD) Imaging tests (SD) Physician visits (SD) Psychiatric hospitalizations (SD) Working days lost (SD) ⁎⁎⁎ pb.001. ⁎ pb.05. ⁎⁎ pb.01.
Non-TRD 51.3 (15.5)
51.7 (16.8)
11 (40.7) 16 (59.3)
27 (33.8) 53 (66.3)
F(1,106) = .011 χ2(1) = .431
χ2(3) = 3.124 6 (22.2) 17 (63) 2 (7.4) 2 (7.4)
18.6 (9.5) 2831.8 1362 54,305.3 48,078.5 56,658
(3219.7) (3277.2) (69,423.5) (66,733) (113,477.8)
12 (15) 43 (53.8) 16 (20) 9 (11.3)
9.8 (9.3) 2301.8 444.8 27,802.4 21,768.5 13,380.8
(2619.4) (916.4) (47,352.1) (43,382.1) (47,266.4)
F(2,107) = 17.69 ⁎⁎⁎ F(5,101) = 2.39 ⁎ F(5,101)=.734 F(5,101) = 5.16 ⁎ F(5,101) = 4.92 ⁎ F(5,101) = 5.55 ⁎ F(5,101) = 7.76 ⁎⁎
674
L. Fostick et al.
Table 2 Pearson correlation between TRD residuals, mean HDRS residuals, and costs.
Blood tests Imaging tests Physician visits Psychiatric hospitalizations Working days lost
TRD residuals
Mean HDRS residuals
.223 ⁎ .213 ⁎ .276 ⁎⁎ .287 ⁎⁎
−.005 .014 −.070 −.073 .030
.171
⁎ pb.05. ⁎⁎ pb.01.
HDRS residuals were not found to be associated with any of the costs.
Future studies should examine the issue of resistance versus severity in a larger sample which will enable to divide TRD and non-TRD patients into high or low severity. The importance of controlling the shared variance of TRD and MDD severity while measuring the economic consequences of TRD was demonstrated in the results of the current study, by a lack of relationship between MDD severity and the economic impact, when the shared variance with TRD controlled. Moreover, the findings on the existence of a relationship between TRD and costs, even after controlling for the shares variance with MDD severity, suggest that TRD might be the main factor in determining the economic burden of depression, rather than MDD severity.
Role of the funding source The study was carried out with no financial support.
4. Discussion The relationship between TRD and the economic consequences was tested taking into account the severity of depression. As was previously reported, TRD was found to be related to MDD severity and also to higher costs of medical services and loss of working days. These results were replicated when the shared variance of TRD with MDD severity was controlled. MDD severity was positively correlated to costs. However, when controlled for the shared variance of MDD severity with TRD, MDD severity was no longer related to financial costs. These results suggest that the relationship observed between MDD severity and costs is related to TRD. Several comprehensive studies in the literature have demonstrated that TRD is costly, mainly due to an extensive use of medical services and also due to the reduction of productivity and to work absenteeism (Crown et al., 2002; Thomas and Morris, 2003; Greenberg et al., 2004). Moreover, it was suggested that medical health care expenditures increase with the degree of TRD, i.e., the number of failed anti-depressive treatments (Crown et al., 2002; Russell et al., 2004). Since MDD can be characterized both by response to treatment and by the severity of the disease, the findings on the relationship between TRD and costs give rise to a question concerning the role of TRD and MDD severity in the economic burden of MDD. The studies that reported analyses of the economic burden of TRD were mainly carried out on medical databases. The advantage of this form of study is in its impressively large population. However, these studies lack the capacity to measure the current severity of the disease in each subject enrolled to the study which is the main contribution of the current study's design. Nevertheless, this study has some limitations. First, the assessment of treatment response was done retrospectively and other variables were collected as self report. This limitation can cause an assessment bias due to misrecollection. In the current study this limitation was somewhat reduced, as the assessment was done during the last episode. Second, the cost of medications is not reflected in the current study. However, as these costs are evaluated to be only 30% of total costs we do not expect the results to change. Third, the number of participants in this study is relatively small.
Contributors Leah Fostick designed the study, wrote the study protocol, analyzed the data, and wrote the paper. Alysa Silberman designed the study and analyzed the data. Marina Beckman interviewed the participants, collected the data, and wrote the paper. Baruch Spivak designed the study and wrote the paper. Daniela Amital designed the study, analyzed the data, and wrote the paper.
Conflict of interest The study had no grant support. The authors had no conflict of interests.
References Monthly Average Wage per Employee Job in 2005. Central Bureau of Statistics, press release no. 47/2006, March 8, 2006. Corey-Lisle, P.K., Birnbaum, H.G., Greenberg, P.E., Marynchenko, M.B., Claxton, A.J., 2002. Identification of a claims data “signature” and economic consequences for treatment-resistant depression. J. Clin. Psychiatry 63 (8), 717–726. Crown, W.H., Finkelstein, S., Berndt, E.R., Ling, D., Poret, A.W., Rush, A.J., Russell, J.M., 2002. The impact of treatmentresistant depression on health care utilization and costs. Clin. Psychiatry 63 (11), 963–971. Fava, M., 2003. Diagnosis and definition of treatment-resistant depression. Biol. Psychiatry 15 (53(8)), 649–659. Fredman, S.J., Fava, M., Kienke, A.S., White, C.N., Nierenberg, A.A., Rosenbaum, J.F., 2000. Partial response, non-response, and relapse with selective serotonin reuptake inhibitors in major depression: a survey of current “next-step” practices. J. Clin. Psychiatry 61 (6), 403–408. Greenberg, P.E., Stiglin, L.E., Finkelstein, S.N., Berndt, E.R., 1993. The economic burden of depression in 1990. J. Clin. Psychiatry 54 (11), 405–418. Greenberg, P.E., Kessler, R.C., Birnbaum, H.G., Leong, S.A., Lowe, S.W., Berglund, P.A., Corey-Lisle, P.K., 2003. The economic burden of depression in the United States: how did it change between 1990 and 2000? J. Clin. Psychiatry 64 (12), 1465–1475. Greenberg, P., Corey-Lisle, P.K., Birnbaum, H., Marynchenko, M., Claxton, A., 2004. Economic implications of treatment-resistant depression among employees. Pharmacoeconomics 22 (6), 363–373.
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Hamilton, M., 1960. A rating scale for depression. J. Neurol. Neurosurg. Psychiatry 23, 56–62. Joyce, P.R., Mulder, R.T., Luty, S.E., McKenzie, J.M., Sullivan, P.F., Abbott, R.M., Stevens, I.F., 2002. Melancholia: definitions, risk factors, personality, neuroendocrine markers and differential antidepressant response. Aust. N. Z. J. Psychiatry 36 (3), 376–383. Kessler, R.C., Borges, G., Walters, E.E., 1999. Prevalence of and risk factors for lifetime suicide attempts in the National Comorbidity Survey. Arch. Gen. Psychiatry 56 (7), 617–626. Kind, P., Sorensen, J., 1993. The costs of depression. Int. Clin. Psychopharmacol. 7 (3–4), 191–195. Kocsis, J.H., 2000. New strategies for treating chronic depression. J. Clin. Psychiatry 61 (Suppl 11), 42–45. Ministry of Health published price list for ambulatory utilization and differential procedures, 2006. Nemeroff, C.B., 2007. Prevalence and management of treatmentresistant depression. J. Clin. Psychiatry 68 (Suppl 8), 17–25. Russell, J.M., Hawkins, K., Ozminkowski, R.J., Orsini, L., Crown, W.H., Kennedy, S., Finkelstein, S., Berndt, E., Rush, A.J., 2004. The cost consequences of treatment-resistant depression. J. Clin. Psychiatry 65 (3), 341–347. Sackeim, H.A., 2001. The definition and meaning of treatmentresistant depression. J. Clin. Psychiatry 62 (Suppl 16), 10–17.
Sheehan, D.V., Lecrubier, Y., Sheehan, K.H., Amorim, P., Janavs, J., Weiller, E., Hergueta, T., Baker, R., Dunbar, G.C., 1998. The MiniInternational Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J. Clin. Psychiatry 59 (Suppl 20), 22–33. Souery, D., Amsterdam, J., de Montigny, C., Lecrubier, Y., Montgomery, S., Lipp, O., Racagni, G., Zohar, J., Mendlewicz, J., 1999. Treatment-resistant depression: methodological overview and operational criteria. Eur. Neuropsychopharmacol. 9 (1–2), 83–91. Souery, D., Oswald, P., Massat, I., Bailer, U., Bollen, J., Demyttenaere, K., Kasper, S., Lecrubier, Y., Montgomery, S., Serretti, A., Zohar, J., Mendlewicz, J., 2007. Clinical factors associated with treatment resistance in major depressive disorder: results from a European multicenter study. J. Clin. Psychiatry 68 (7), 1062–1070. Stewart, W.F., Ricci, J.A., Chee, E., Hahn, S.R., Morganstein, D., 2003. Cost of lost productive work time among US workers with depression. JAMA 289 (23), 3135–3144. Thase, M.E., Rush, A.J., 1997. When at first you don't succeed: sequential strategies for antidepressant non-responders. J. Clin. Psychiatry 58 (Suppl 13), 23–29. Thomas, C.M., Morris, S., 2003. Cost of depression among adults in England in 2000. Br. J. Psychiatry 183, 514–519. Tierney, J.G., 2007. Treatment-resistant depression: managed care considerations. J. Manag. Care Pharm. 13 (6 Suppl A), S2–S7.
www.elsevier.com/locate/euroneuro
The economic impact of depression: Resistance or severity? L. Fostick a,⁎, A. Silberman b , M. Beckman c , B. Spivak c , D. Amital c a
Ariel University Center of Samaria, Israel Department of Psychiatry, Chaim Sheba Medical Center, Israel c Ness-Ziona Mental Health Center, Israel b
Received 18 April 2010; received in revised form 3 June 2010; accepted 9 June 2010
KEYWORDS Major Depressive Disorder (MDD); Treatment-Resistant Depression (TRD); Severity; Economic burden
Abstract Treatment-Resistant Depression (TRD) affects 60 to 70% of patients with Major Depressive Disorder (MDD). The economic impact of depression in general, and of TRD specifically, was found to be relatively high. As the course of depression can be defined both by the severity of the disease and by the resistance to treatment, the question of the unique contribution of MDD severity vs. resistance to the economic burden of depression is being raised. One hundred and seven unipolar MDD patients, all treated for at least 4 weeks, were enrolled in the study. Patients were assessed for their current MDD severity using the Hamilton Depression Rating Scale (HDRS) and past treatments, and for medical-related costs (number of blood and imaging tests, visits paid to physicians, psychiatric hospitalizations) and incapacity-related costs (number of working days lost) during the last episode. TRD and non-TRD patients were, respectively, 39.3% and 60.7% of the patients recruited for the study. TRD patients had more severe depression, and higher costs for imaging tests, physician visits, psychiatric hospitalizations, and number of working days lost. In addition, higher MDD severity was found to be associated with higher costs. Finally, when controlling for the shared variance of TRD and MDD severity, by using residual scores, TRD was associated with higher costs, but MDD severity was no longer related to costs. While both resistance and severity are associated with higher direct and indirect costs, our findings suggest that TRD may be the main factor in determining the economic burden of depression. © 2010 Elsevier B.V. and ECNP. All rights reserved.
1. Introduction
⁎ Corresponding author. Department of Communication Disorders, Ariel University Center of Samaria, 40700, Israel. Tel.: +972 3 9765776; fax: +972 3 9765743. E-mail address: [email protected] (L. Fostick).
Treatment-Resistant Depression (TRD) is a major publichealth problem, affecting the suffering patient, his close relatives, and society as a whole (Crown et al., 2002). TRD 12-month prevalence is estimated to be 2–3% (figures vary according to definition) (Nemeroff, 2007). Despite rapid
0924-977X/$ - see front matter © 2010 Elsevier B.V. and ECNP. All rights reserved. doi:10.1016/j.euroneuro.2010.06.001
672 development in the therapeutic tools of mood disorders since the late 1980s (Fredman et al., 2000; Kocsis, 2000), 60 to 70% of Major Depressive Disorder (MDD) patients fail to reach complete remission even when adequately treated (Sackeim, 2001). Moreover, about half of those who do respond to treatment and exhibit substantial decrease in their symptomatology continue to have significant residual symptoms that affect their functioning and quality of life. Therefore, TRD results in a substantial burden of escalating medical mental health costs and suffering. The economic burden of depression is a subject of public interest and is measured nationally among the economic burdens of other diseases. Not surprisingly, the economic burden of depression is very high, estimated at $83.1 billion in the US in 2000 (Greenberg et al., 2003), and at 7 billion pounds in the UK in 2000 (Thomas and Morris, 2003). More specifically, investigators who focused on the economic burden of TRD have estimated its costs to be approximately $11,000 to $14,000 per year (Corey-Lisle et al., 2002; Crown et al., 2002; Russell et al., 2004). While evaluating the economic cost of depression on society, investigators usually separate between direct costs, which are costs due to the treatment of depression, and indirect costs, which are costs due to the impact of depression, such as loss of work productivity (work absenteeism and reduction of productivity within the work place) and suicide (Thomas and Morris, 2003; Kind and Sorensen, 1993; Greenberg et al., 1993). For example, of the total costs for depression estimated in the US in 2000, 31% ($26.1 billion) was related to direct medical costs, 7% ($5.4 billion) was related to suicide-related mortality costs, and 62% ($51.5 billion) was related to workplace costs (Greenberg et al., 1993). Work absenteeism is considered to be a major contributor to the economic burden of depression (Tierney, 2007). Along this line, Kessler et al. (1999) suggest that the costs of depression-related work absenteeism for a period of thirty days, alone, are almost as expensive as the total costs for successful treatment of depression. However, the studies that measure the impact of depression on work do not include estimates for the cost of loss of productivity while at work. Stewart et al. (2003) estimated an excess loss of productivity of $44 billion in the USA during 2000, solely due to the loss of productivity at the work place, without taking into account work absenteeism or disability pensions. Depression can take different courses. Whether moderate or severe, it may respond well to treatment, and therefore be of short duration. Conversely, it can last for years with no response, or more frequently with partial response to different treatment regimens. Depression severity and resistance may be considered to be separate and overlapping factors. Fava (2003) suggested that MDD with psychotic features, which might be considered a severe form of depression, is associated with poor treatment outcome, therefore causes a treatment resistant form of depression. However, some researchers have found melancholic depression, which can also be considered a severe form of depression, does not seem to be associated with poor response, and therefore causes a severe, but not resistant, form of depression (Joyce et al., 2002), while others have found both melancholia and MDD severity to be associated with TRD (Souery et al., 2007). The partition between these
L. Fostick et al. two forms of depression raises the question whether the relatively large economic burden of depression is related to the severity of the depression, i.e. to the magnitude of functional impairment and loss of productivity, or rather to the chronicity of the disease among the significant number of the patients who are resistant to treatment? Reviewing the existing literature on the economic impact of depression, this question remains unanswered. The literature employs different definitions of TRD, based the number of failed adequate treatments the patient received (Thase and Rush, 1997; Fava, 2003; Souery et al., 1999). In 2002, the European Union's Committee for Propriety Medicinal Products (CPMP) defined TRD as a failure to respond to the second treatment of two consecutive products of different classes given at an adequate dose and for a sufficient length of time. This definition was adopted in the current study as it enables the differentiation of MDD patients into two groups, according to their response to treatment. In the current study we aim to explore the economic impact of TRD, focusing on both direct and indirect costs. As opposed to previous studies that addressed this issue (e.g., Crown et al., 2002; Russell et al., 2004; Greenberg et al., 2003, 2004), the current study reports not only on costs related to TRD, but also on individual data of the severity of depression drawn from clinical interviews with each of the participants. These unique set of data will enable us to explore the differential contribution of chronicity vs. severity in the economic burden of TRD.
2. Experimental procedures Participants. The participants in this study were identified during 2005 from the registry of four community psychiatric outpatient clinics, providing psychiatric care to about 10,000 people. Among them, a total of 150 potential participants were found to meet the following inclusion criteria: lifetime diagnosis of unipolar depression according to ICD-10 (F32, F33); at least one adequate treatment, i.e., an optimal dose of the medication, according to the product datasheet, provided for a duration of at least 4 weeks (both responders and non-responders) during their last depressive episode; and no diagnosis of bipolar disorder, schizophrenia, severe neurological problems, or mental retardation. These criteria, along with demographics, were evaluated through medical records. The study psychiatrist (MB) called all 150 eligible patients by telephone. Among them, a total of 107 patients agreed to participate in the study and were invited to the clinic for an interview with the psychiatrist. Participants received a full explanation about the study and signed a written informed consent prior to the interview. The study protocol was approved by the local ethics committee. Assessment. All clinical ratings were administered during a single interview by the study psychiatrist (MB) who was trained in the study procedure and was blind to the study aim. The interviews lasted for 45–60 min and took place after consultation with each patient's psychiatrist. To assess the current disorder, we used the Mini International Neuropsychiatric Interview (MINI; Sheehan et al., 1998) to verify current and lifetime diagnosis. Depression symptoms were evaluated by the 17-item Hamilton Depression Rating Scale (HDRS; Hamilton, 1960). Direct (medical-related) and indirect (incapacity-related) costs were assessed using a self-rating questionnaire, in which each patient indicated the number of blood and imaging tests he undertook, the number of physician visits, the number of psychiatric
The economic impact of depression: Resistance or severity? hospitalizations, and the number of working days lost during the last episode. Treatment costs were calculated based on the price list for medical utilization published by the Israeli Ministry Of Health (MOH) (MOH, 2006), combined with the patients' reported usage of MOH services. Workplace costs were calculated by multiplying the average missed working days per month during the current episode reported by the patient with the average income in Israel, which was $1633 per month in 2005 according to the Israeli Central Bureau of Statistics (CBS, 2006). MDD severity was evaluated using the Hamilton Depression Rating Scale (HDRS; Hamilton, 1960). The participants were divided into two groups according to their response to treatment. A failure to respond to the current treatment was defined as HDRS ≥ 17 at least after 4 weeks of treatment in an optimal dose, and a failure to respond to previous treatment trials was identified by change of treatment. TRD patients were those who did not respond to two or more treatments from different mechanisms of action.
3. Results Table 1 presents TRD and non-TRD patients' demographic data (age, sex, and marital status), mean HDRS score, and costs (number of blood tests, number of imaging tests, number of physician visits, number of psychiatric hospitalizations, and number of working days lost during the last episode).
3.1. TRD and severity Age, sex and marital status did not differ between TRD and non-TRD patients. In order to test differences between TRD and non-TRD patients in severity measures, a Multivariate Analysis of Variance (MANOVA) was conducted with mean HDRS score as the dependent variable. MDD severity was found to be significantly different between TRD and non-TRD patients. Mean HDRS score was found to be higher among TRD (18.6) vs. non-TRD (9.8) patients.
Table 1
673
3.2. TRD and costs The difference between TRD and non-TRD patients in direct and indirect costs was analyzed using MANOVA, with total costs of blood tests, imaging tests, physician visits, psychiatric hospitalizations, and working days lost as the dependent variables. Overall, there was a significant difference between TRD and non-TRD patients in direct and indirect costs. When analyzing each parameter separately, costs for imaging tests, physician visits, psychiatric hospitalizations, and number of working days lost were found to be higher among the TRD group.
3.3. MDD severity and costs The relationship between MDD severity, as measured by HDRS, and costs, was measured using Pearson correlations between mean HDRS score and total costs of blood tests, imaging tests, physician visits, psychiatric hospitalizations, and working days lost. MDD severity was found to be associated with costs, as was reflected in significant positive correlations between mean HDRS score and all cost categories (Table 2).
3.4. TRD severity and costs As can be seen in Table 1, MDD severity is related to TRD so that higher severity was found among TRD patients. In order to estimate the contribution of TRD and MDD severity to costs, controlling for their shared variance (multicolinearity), we analyzed the relationship between costs and the residual scores for TRD and mean HDRS scores. Table 2 presents correlations between TRD residuals, mean HDRS residuals, and costs. TRD residuals were found to be significantly correlated with costs for blood tests, imaging tests, psychiatric hospitalizations, and physician visits, but not for working days lost. However, mean
Demographics, MDD severity, and costs, for TRD and non-TRD patients. TRD
Demographics Mean age (SD) Sex No. males (%) No. females (%) Marital status No. Single (%) No. married (%) No. divorced (%) No. widow/er (%) MDD severity Mean HDRS score Costs (in NIS) Blood tests (SD) Imaging tests (SD) Physician visits (SD) Psychiatric hospitalizations (SD) Working days lost (SD) ⁎⁎⁎ pb.001. ⁎ pb.05. ⁎⁎ pb.01.
Non-TRD 51.3 (15.5)
51.7 (16.8)
11 (40.7) 16 (59.3)
27 (33.8) 53 (66.3)
F(1,106) = .011 χ2(1) = .431
χ2(3) = 3.124 6 (22.2) 17 (63) 2 (7.4) 2 (7.4)
18.6 (9.5) 2831.8 1362 54,305.3 48,078.5 56,658
(3219.7) (3277.2) (69,423.5) (66,733) (113,477.8)
12 (15) 43 (53.8) 16 (20) 9 (11.3)
9.8 (9.3) 2301.8 444.8 27,802.4 21,768.5 13,380.8
(2619.4) (916.4) (47,352.1) (43,382.1) (47,266.4)
F(2,107) = 17.69 ⁎⁎⁎ F(5,101) = 2.39 ⁎ F(5,101)=.734 F(5,101) = 5.16 ⁎ F(5,101) = 4.92 ⁎ F(5,101) = 5.55 ⁎ F(5,101) = 7.76 ⁎⁎
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Table 2 Pearson correlation between TRD residuals, mean HDRS residuals, and costs.
Blood tests Imaging tests Physician visits Psychiatric hospitalizations Working days lost
TRD residuals
Mean HDRS residuals
.223 ⁎ .213 ⁎ .276 ⁎⁎ .287 ⁎⁎
−.005 .014 −.070 −.073 .030
.171
⁎ pb.05. ⁎⁎ pb.01.
HDRS residuals were not found to be associated with any of the costs.
Future studies should examine the issue of resistance versus severity in a larger sample which will enable to divide TRD and non-TRD patients into high or low severity. The importance of controlling the shared variance of TRD and MDD severity while measuring the economic consequences of TRD was demonstrated in the results of the current study, by a lack of relationship between MDD severity and the economic impact, when the shared variance with TRD controlled. Moreover, the findings on the existence of a relationship between TRD and costs, even after controlling for the shares variance with MDD severity, suggest that TRD might be the main factor in determining the economic burden of depression, rather than MDD severity.
Role of the funding source The study was carried out with no financial support.
4. Discussion The relationship between TRD and the economic consequences was tested taking into account the severity of depression. As was previously reported, TRD was found to be related to MDD severity and also to higher costs of medical services and loss of working days. These results were replicated when the shared variance of TRD with MDD severity was controlled. MDD severity was positively correlated to costs. However, when controlled for the shared variance of MDD severity with TRD, MDD severity was no longer related to financial costs. These results suggest that the relationship observed between MDD severity and costs is related to TRD. Several comprehensive studies in the literature have demonstrated that TRD is costly, mainly due to an extensive use of medical services and also due to the reduction of productivity and to work absenteeism (Crown et al., 2002; Thomas and Morris, 2003; Greenberg et al., 2004). Moreover, it was suggested that medical health care expenditures increase with the degree of TRD, i.e., the number of failed anti-depressive treatments (Crown et al., 2002; Russell et al., 2004). Since MDD can be characterized both by response to treatment and by the severity of the disease, the findings on the relationship between TRD and costs give rise to a question concerning the role of TRD and MDD severity in the economic burden of MDD. The studies that reported analyses of the economic burden of TRD were mainly carried out on medical databases. The advantage of this form of study is in its impressively large population. However, these studies lack the capacity to measure the current severity of the disease in each subject enrolled to the study which is the main contribution of the current study's design. Nevertheless, this study has some limitations. First, the assessment of treatment response was done retrospectively and other variables were collected as self report. This limitation can cause an assessment bias due to misrecollection. In the current study this limitation was somewhat reduced, as the assessment was done during the last episode. Second, the cost of medications is not reflected in the current study. However, as these costs are evaluated to be only 30% of total costs we do not expect the results to change. Third, the number of participants in this study is relatively small.
Contributors Leah Fostick designed the study, wrote the study protocol, analyzed the data, and wrote the paper. Alysa Silberman designed the study and analyzed the data. Marina Beckman interviewed the participants, collected the data, and wrote the paper. Baruch Spivak designed the study and wrote the paper. Daniela Amital designed the study, analyzed the data, and wrote the paper.
Conflict of interest The study had no grant support. The authors had no conflict of interests.
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